mount_dir = '/Volumes/spacetop_projects_cue/analysis/fmri/spm/univariate/model01_6cond_highlowcue_rampplateau/1stlevel';
'P_VC_STIM_cue_high_gt_low', 'V_PC_STIM_cue_high_gt_low', 'C_PV_STIM_cue_high_gt_low',...% contratss
'P_VC_STIM_stimlin_high_gt_low', 'V_PC_STIM_stimlin_high_gt_low', 'C_PV_STIM_stimlin_high_gt_low',...
'P_VC_STIM_stimquad_med_gt_other', 'V_PC_STIM_stimquad_med_gt_other', 'C_PV_STIM_stimquad_med_gt_other',...
'P_VC_STIM_cue_int_stimlin','V_PC_STIM_cue_int_stimlin', 'C_PV_STIM_cue_int_stimlin',...
'P_VC_STIM_cue_int_stimquad','V_PC_STIM_cue_int_stimquad','C_PV_STIM_cue_int_stimquad',...
'P_simple_STIM_cue_high_gt_low','V_simple_STIM_cue_high_gt_low', 'C_simple_STIM_cue_high_gt_low',... % dummay contrasts
'P_simple_STIM_stimlin_high_gt_low', 'V_simple_STIM_stimlin_high_gt_low', 'C_simple_STIM_stimlin_high_gt_low',...
'P_simple_STIM_stimquad_med_gt_other','V_simple_STIM_stimquad_med_gt_other', 'C_simple_STIM_stimquad_med_gt_other',...
'P_simple_STIM_cue_int_stimlin', 'V_simple_STIM_cue_int_stimlin', 'C_simple_STIM_cue_int_stimlin',...
'P_simple_STIM_cue_int_stimquad', 'V_simple_STIM_cue_int_stimquad','C_simple_STIM_cue_int_stimquad',...
'P_simple_STIM_highcue_highstim', 'P_simple_STIM_highcue_medstim', 'P_simple_STIM_highcue_lowstim',... % pain events
'P_simple_STIM_lowcue_highstim', 'P_simple_STIM_lowcue_medstim', 'P_simple_STIM_lowcue_lowstim',...
'V_simple_STIM_highcue_highstim', 'V_simple_STIM_highcue_medstim', 'V_simple_STIM_highcue_lowstim',... % vicarious events
'V_simple_STIM_lowcue_highstim', 'V_simple_STIM_lowcue_medstim', 'V_simple_STIM_lowcue_lowstim',...
'C_simple_STIM_highcue_highstim', 'C_simple_STIM_highcue_medstim', 'C_simple_STIM_highcue_lowstim',... % cognitive events
'C_simple_STIM_lowcue_highstim', 'C_simple_STIM_lowcue_medstim', 'C_simple_STIM_lowcue_lowstim',...
'P_VC_CUE_cue_high_gt_low','V_PC_CUE_cue_high_gt_low','C_PV_CUE_cue_high_gt_low',...% cue epoch contrasts
'P_simple_CUE_cue_high_gt_low','V_simple_CUE_STIM_cue_high_gt_low','C_simple_CUE_cue_high_gt_low',...% cue epoch dummy
'G_simple_CUE_cue_high_gt_low',...
'P_VC_STIM', 'V_PC_STIM', 'C_PV_STIM'
index = find(strcmp(contrast_name, contrast_of_interest));
con_name = sprintf('*con_%04d.nii', index);
con_list = dir(fullfile(mount_dir, '*', con_name));
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
Direct calls to spm_defauts are deprecated.
Please use spm('Defaults',modality) or spm_get_defaults instead.
loading mask. mapping volumes.
checking that dimensions and voxel sizes of volumes are the same.
Pre-allocating data array. Needed: 28753056 bytes
Loading image number: 72
Elapsed time is 9.633443 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 6899522 Bit rate: 22.72 bits
%for s = 1:length(wh_outlier_corr)
%disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:);
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:);
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:);
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))));
after removing 2 participants, size is now 70
beh_cueeffect = readtable('/Users/h/Documents/projects_local/cue_expectancy/data/hlm/cue_stim_effects_scaling.csv')
beh_cueeffect = 342×22 table
| | sub | task | cue_raw_outcome | cue_raw_outcome_sd | cue_z_outcome | cue_z_outcome_sd | cue_raw_expect | cue_raw_expect_sd | cue_z_expect | cue_z_expect_sd | stim_raw_outcome | stim_raw_outcome_sd | stim_z_outcome | stim_z_outcome_sd | stim_raw_expect | stim_raw_expect_sd | stim_z_expect | stim_z_expect_sd | cuestim_raw_outcome | cuestim_raw_outcome_reg | cuestim_z_outcome | cuestim_z_outcome_reg |
|---|
| 1 | 'sub-0002' | 'cognitive' | 4.5409 | 6.3433 | 0.1217 | 0.1701 | 23.9035 | 18.7340 | 0.5964 | 0.4674 | 4.4897 | 10.0404 | 0.1204 | 0.2692 | -3.3434 | 20.1072 | -0.0834 | 0.5017 | 1.0114 | 1.0093 | 1.0114 | 1.0012 |
|---|
| 2 | 'sub-0003' | 'cognitive' | 7.6366 | 17.1034 | 0.4716 | 1.0562 | 30.1550 | 25.1770 | 1.2606 | 1.0525 | 4.0612 | 11.0291 | 0.2508 | 0.6811 | -4.2852 | 7.4098 | -0.1791 | 0.3098 | 1.8804 | 1.7064 | 1.8804 | 1.1765 |
|---|
| 3 | 'sub-0004' | 'cognitive' | 1.6275 | 7.6327 | 0.0707 | 0.3315 | 33.7740 | 25.3429 | 1.0873 | 0.8159 | 0.9330 | 6.2388 | 0.0405 | 0.2710 | -1.0311 | 9.8240 | -0.0332 | 0.3163 | 1.7444 | 1.3593 | 1.7444 | 1.0290 |
|---|
| 4 | 'sub-0005' | 'cognitive' | 13.1310 | 41.4426 | 0.3330 | 1.0511 | 41.7857 | 37.3601 | 1.2517 | 1.1191 | 4.6719 | 29.8296 | 0.1185 | 0.7566 | -2.9590 | 8.8393 | -0.0886 | 0.2648 | 2.8107 | 2.4914 | 2.8107 | 1.1918 |
|---|
| 5 | 'sub-0006' | 'cognitive' | 5.1484 | 28.9467 | 0.1557 | 0.8753 | 30.5626 | 19.9891 | 1.0611 | 0.6940 | 15.8651 | 28.8580 | 0.4797 | 0.8726 | 7.0583 | 18.4669 | 0.2451 | 0.6412 | 0.3245 | 0.3646 | 0.3245 | 0.7810 |
|---|
| 6 | 'sub-0007' | 'cognitive' | 14.0767 | 9.6271 | 0.6350 | 0.4343 | 29.3246 | 11.5759 | 1.1869 | 0.4685 | 12.5187 | 11.4510 | 0.5647 | 0.5165 | -4.4602 | 9.2611 | -0.1805 | 0.3749 | 1.1244 | 1.1152 | 1.1244 | 1.0449 |
|---|
| 7 | 'sub-0008' | 'cognitive' | 2.3703 | 12.2756 | 0.1446 | 0.7491 | 6.1256 | 10.0998 | 0.4525 | 0.7460 | 13.7493 | 21.4645 | 0.8391 | 1.3099 | -1.9910 | 7.1383 | -0.1471 | 0.5273 | 0.1724 | 0.2285 | 0.1724 | 0.6224 |
|---|
| 8 | 'sub-0009' | 'cognitive' | 9.5909 | 7.9866 | 0.1485 | 0.1237 | 38.1809 | 8.9126 | 0.6078 | 0.1419 | 7.4610 | 8.1527 | 0.1155 | 0.1262 | 0.4258 | 11.4016 | 0.0068 | 0.1815 | 1.2855 | 1.2517 | 1.2855 | 1.0296 |
|---|
| 9 | 'sub-0010' | 'cognitive' | 9.2561 | 9.1427 | 0.4399 | 0.4345 | 36.3668 | 10.1528 | 1.4257 | 0.3980 | 12.3921 | 10.9235 | 0.5889 | 0.5191 | -7.9591 | 11.9403 | -0.3120 | 0.4681 | 0.7469 | 0.7658 | 0.7469 | 0.9062 |
|---|
| 10 | 'sub-0011' | 'cognitive' | 17.0180 | 22.7796 | 0.4731 | 0.6333 | 45.6624 | 19.7596 | 1.2666 | 0.5481 | 11.7768 | 24.3125 | 0.3274 | 0.6760 | -6.3037 | 14.4209 | -0.1749 | 0.4000 | 1.4450 | 1.4102 | 1.4450 | 1.1098 |
|---|
| 11 | 'sub-0013' | 'cognitive' | 16.0887 | 22.0632 | 0.3582 | 0.4913 | 59.3561 | 12.5922 | 1.2895 | 0.2736 | 14.9900 | 25.6619 | 0.3338 | 0.5714 | -2.3620 | 10.9018 | -0.0513 | 0.2368 | 1.0733 | 1.0687 | 1.0733 | 1.0183 |
|---|
| 12 | 'sub-0014' | 'cognitive' | 3.7832 | 10.7579 | 0.1378 | 0.3919 | 27.9490 | 16.7531 | 0.9790 | 0.5868 | 9.4585 | 9.6178 | 0.3445 | 0.3503 | -0.9995 | 8.3669 | -0.0350 | 0.2931 | 0.4000 | 0.4574 | 0.4000 | 0.8462 |
|---|
| 13 | 'sub-0015' | 'cognitive' | 32.9607 | 38.6649 | 0.5388 | 0.6321 | 55.2081 | 25.4030 | 0.9947 | 0.4577 | -14.9781 | 15.5663 | -0.2448 | 0.2545 | -12.8588 | 27.6116 | -0.2317 | 0.4975 | -2.2006 | -2.4296 | -2.2006 | 2.0377 |
|---|
| 14 | 'sub-0016' | 'cognitive' | 2.3237 | 6.0431 | 0.0816 | 0.2122 | 10.0844 | 15.7012 | 0.3300 | 0.5138 | 3.6519 | 5.7583 | 0.1282 | 0.2022 | -3.1006 | 4.3430 | -0.1015 | 0.1421 | 0.6363 | 0.7145 | 0.6363 | 0.9587 |
|---|
| 15 | 'sub-0017' | 'cognitive' | 6.6921 | 25.3397 | 0.2755 | 1.0432 | 51.4338 | 23.0910 | 1.4946 | 0.6710 | 4.1942 | 16.5694 | 0.1727 | 0.6821 | -9.4427 | 23.2133 | -0.2744 | 0.6746 | 1.5955 | 1.4809 | 1.5955 | 1.0877 |
|---|
| 16 | 'sub-0018' | 'cognitive' | -2.7493 | 11.1383 | -0.1245 | 0.5045 | 21.1337 | 8.8817 | 1.3631 | 0.5728 | 9.0266 | 17.8361 | 0.4089 | 0.8079 | 0.1670 | 7.7627 | 0.0108 | 0.5007 | -0.3046 | -0.1745 | -0.3046 | 0.6214 |
|---|
| 17 | 'sub-0019' | 'cognitive' | 8.0487 | 7.4358 | 0.5274 | 0.4873 | 15.4708 | 8.8400 | 1.2149 | 0.6942 | 0.8349 | 5.5711 | 0.0547 | 0.3651 | 1.7750 | 9.8468 | 0.1394 | 0.7733 | 9.6409 | 4.9316 | 9.6409 | 1.4482 |
|---|
| 18 | 'sub-0020' | 'cognitive' | 15.2624 | 22.1884 | 0.5532 | 0.8043 | 19.7965 | 16.0291 | 0.8584 | 0.6950 | 27.6029 | 16.8160 | 1.0005 | 0.6095 | 3.4965 | 17.5109 | 0.1516 | 0.7593 | 0.5529 | 0.5686 | 0.5529 | 0.7764 |
|---|
| 19 | 'sub-0021' | 'cognitive' | -5.0078 | 14.2768 | -0.1653 | 0.4711 | 43.5394 | 21.2512 | 1.5957 | 0.7788 | 2.0232 | 9.4353 | 0.0668 | 0.3114 | -12.4701 | 26.1608 | -0.4570 | 0.9588 | -2.4752 | -1.3257 | -2.4752 | 0.7825 |
|---|
| 20 | 'sub-0023' | 'cognitive' | 9.5442 | 25.4940 | 0.2939 | 0.7849 | 45.6580 | 10.3519 | 1.5517 | 0.3518 | 16.3559 | 27.0526 | 0.5036 | 0.8329 | -4.1672 | 9.7799 | -0.1416 | 0.3324 | 0.5835 | 0.6075 | 0.5835 | 0.8605 |
|---|
| 21 | 'sub-0024' | 'cognitive' | 2.6437 | 14.2966 | 0.1109 | 0.5998 | 44.6227 | 9.1297 | 1.4345 | 0.2935 | 11.3381 | 9.2045 | 0.4757 | 0.3862 | -1.5656 | 9.3068 | -0.0503 | 0.2992 | 0.2332 | 0.2953 | 0.2332 | 0.7528 |
|---|
| 22 | 'sub-0025' | 'cognitive' | 11.8852 | 29.9382 | 0.4586 | 1.1552 | 37.6042 | 10.3834 | 1.5255 | 0.4212 | 19.1130 | 19.2974 | 0.7375 | 0.7446 | -4.9459 | 8.9225 | -0.2006 | 0.3620 | 0.6218 | 0.6406 | 0.6218 | 0.8395 |
|---|
| 23 | 'sub-0026' | 'cognitive' | 1.3768 | 21.8052 | 0.0585 | 0.9265 | 30.4905 | 10.3718 | 1.6754 | 0.5699 | 15.7734 | 17.3002 | 0.6702 | 0.7351 | 2.1291 | 7.0095 | 0.1170 | 0.3852 | 0.0873 | 0.1417 | 0.0873 | 0.6337 |
|---|
| 24 | 'sub-0028' | 'cognitive' | 9.3625 | 25.5844 | 0.2210 | 0.6040 | 58.0384 | 13.7303 | 1.6567 | 0.3919 | 11.5875 | 10.7670 | 0.2736 | 0.2542 | -14.1632 | 17.1093 | -0.4043 | 0.4884 | 0.8080 | 0.8232 | 0.8080 | 0.9588 |
|---|
| 25 | 'sub-0029' | 'cognitive' | 0.3703 | 8.2310 | 0.0397 | 0.8821 | 11.2044 | 6.3265 | 1.2111 | 0.6839 | 5.6618 | 5.2585 | 0.6067 | 0.5635 | -1.8170 | 4.8322 | -0.1964 | 0.5223 | 0.0654 | 0.2057 | 0.0654 | 0.6471 |
|---|
| 26 | 'sub-0030' | 'cognitive' | 5.2027 | 9.4034 | 0.2029 | 0.3667 | 46.5594 | 14.1345 | 1.7039 | 0.5173 | 21.3036 | 11.2007 | 0.8308 | 0.4368 | 0.3936 | 24.7110 | 0.0144 | 0.9043 | 0.2442 | 0.2781 | 0.2442 | 0.6570 |
|---|
| 27 | 'sub-0031' | 'cognitive' | 6.4671 | 22.4301 | 0.2107 | 0.7307 | 19.1461 | 19.2756 | 0.6438 | 0.6482 | 6.0688 | 23.4958 | 0.1977 | 0.7654 | -8.3329 | 13.9642 | -0.2802 | 0.4696 | 1.0656 | 1.0563 | 1.0656 | 1.0108 |
|---|
| 28 | 'sub-0032' | 'cognitive' | 17.8449 | 34.9038 | 0.3046 | 0.5958 | 58.6200 | 18.1226 | 1.2923 | 0.3995 | 1.0190 | 24.5373 | 0.0174 | 0.4188 | -7.8451 | 24.1689 | -0.1729 | 0.5328 | 17.5130 | 9.3340 | 17.5130 | 1.2823 |
|---|
| 29 | 'sub-0033' | 'cognitive' | 16.8996 | 19.9783 | 0.6422 | 0.7592 | 40.9583 | 10.0746 | 1.4552 | 0.3579 | 12.0902 | 20.7746 | 0.4595 | 0.7895 | -7.0495 | 12.7113 | -0.2505 | 0.4516 | 1.3978 | 1.3674 | 1.3978 | 1.1252 |
|---|
| 30 | 'sub-0034' | 'cognitive' | 11.2584 | 29.1155 | 0.3031 | 0.7838 | 57.8757 | 16.0415 | 1.4420 | 0.3997 | 15.8252 | 25.5931 | 0.4260 | 0.6890 | 10.2337 | 22.9155 | 0.2550 | 0.5709 | 0.7114 | 0.7286 | 0.7114 | 0.9138 |
|---|
| 31 | 'sub-0035' | 'cognitive' | -1.8335 | 18.2830 | -0.0680 | 0.6781 | 38.4790 | 9.1027 | 1.5829 | 0.3745 | 13.6443 | 28.8570 | 0.5061 | 1.0703 | -0.3969 | 9.9809 | -0.0163 | 0.4106 | -0.1344 | -0.0569 | -0.1344 | 0.6188 |
|---|
| 32 | 'sub-0036' | 'cognitive' | 10.9788 | 14.1321 | 0.4203 | 0.5411 | 37.3055 | 21.6606 | 1.1782 | 0.6841 | 10.4358 | 16.0444 | 0.3995 | 0.6143 | -20.6941 | 26.7478 | -0.6536 | 0.8447 | 1.0520 | 1.0475 | 1.0520 | 1.0149 |
|---|
| 33 | 'sub-0037' | 'cognitive' | 4.6192 | 26.6138 | 0.1398 | 0.8054 | 51.9544 | 9.3272 | 1.5867 | 0.2849 | 19.5474 | 25.2703 | 0.5915 | 0.7647 | -3.5263 | 10.1725 | -0.1077 | 0.3107 | 0.2363 | 0.2735 | 0.2363 | 0.7162 |
|---|
| 34 | 'sub-0038' | 'cognitive' | 10.5777 | 14.7590 | 0.2663 | 0.3716 | 31.9045 | 12.9581 | 0.9263 | 0.3762 | 12.8137 | 10.7034 | 0.3226 | 0.2695 | -9.1417 | 13.0254 | -0.2654 | 0.3782 | 0.8255 | 0.8381 | 0.8255 | 0.9574 |
|---|
| 35 | 'sub-0039' | 'cognitive' | 6.6283 | 15.2580 | 0.3100 | 0.7135 | 21.1286 | 16.1071 | 1.0728 | 0.8178 | 8.7354 | 10.2522 | 0.4085 | 0.4794 | -3.6555 | 8.6611 | -0.1856 | 0.4398 | 0.7588 | 0.7836 | 0.7588 | 0.9300 |
|---|
| 36 | 'sub-0040' | 'cognitive' | 10.3504 | 17.5835 | 0.3034 | 0.5154 | 45.0014 | 19.7623 | 1.1892 | 0.5223 | 10.1713 | 16.7054 | 0.2982 | 0.4897 | -2.6772 | 22.1902 | -0.0707 | 0.5864 | 1.0176 | 1.0160 | 1.0176 | 1.0040 |
|---|
| 37 | 'sub-0041' | 'cognitive' | 13.7902 | 18.9941 | 0.3501 | 0.4822 | 25.4143 | 7.0173 | 0.6967 | 0.1924 | 11.2594 | 13.5894 | 0.2858 | 0.3450 | -4.3325 | 6.0502 | -0.1188 | 0.1659 | 1.2248 | 1.2064 | 1.2248 | 1.0500 |
|---|
| 38 | 'sub-0043' | 'cognitive' | 5.5640 | 14.2011 | 0.1029 | 0.2626 | 25.8763 | 21.0335 | 0.6365 | 0.5174 | 13.7819 | 23.6790 | 0.2549 | 0.4379 | -4.8207 | 13.2506 | -0.1186 | 0.3259 | 0.4037 | 0.4441 | 0.4037 | 0.8789 |
|---|
| 39 | 'sub-0044' | 'cognitive' | 8.0835 | 12.1030 | 0.2121 | 0.3175 | 50.9883 | 19.2964 | 1.3507 | 0.5112 | 11.6124 | 14.7772 | 0.3046 | 0.3877 | 0.3443 | 11.4709 | 0.0091 | 0.3039 | 0.6961 | 0.7202 | 0.6961 | 0.9290 |
|---|
| 40 | 'sub-0046' | 'cognitive' | 24.7925 | 19.2498 | 0.4288 | 0.3329 | 49.1977 | 22.1586 | 0.9517 | 0.4287 | 26.6805 | 27.6915 | 0.4614 | 0.4789 | 7.1905 | 21.0599 | 0.1391 | 0.4074 | 0.9292 | 0.9318 | 0.9292 | 0.9777 |
|---|
| 41 | 'sub-0047' | 'cognitive' | -4.1902 | 17.3474 | -0.1015 | 0.4204 | 2.3954 | 22.1745 | 0.0784 | 0.7256 | 24.9983 | 24.1791 | 0.6058 | 0.5859 | 2.4407 | 21.5946 | 0.0799 | 0.7066 | -0.1676 | -0.1227 | -0.1676 | 0.5595 |
|---|
| 42 | 'sub-0050' | 'cognitive' | 5.1546 | 14.6209 | 0.0744 | 0.2110 | 33.7267 | 17.3894 | 0.5366 | 0.2766 | 5.5113 | 8.7623 | 0.0795 | 0.1264 | -4.4942 | 7.7864 | -0.0715 | 0.1239 | 0.9353 | 0.9452 | 0.9353 | 0.9952 |
|---|
| 43 | 'sub-0051' | 'cognitive' | 15.1357 | 21.4908 | 0.4811 | 0.6831 | 39.9124 | 19.9648 | 1.3098 | 0.6552 | 1.3853 | 23.4025 | 0.0440 | 0.7439 | -3.7106 | 19.0527 | -0.1218 | 0.6253 | 10.9260 | 6.7647 | 10.9260 | 1.4187 |
|---|
| 44 | 'sub-0052' | 'cognitive' | 13.3010 | 14.8627 | 0.6865 | 0.7671 | 39.8369 | 14.0308 | 1.5754 | 0.5549 | 3.2738 | 16.8655 | 0.1690 | 0.8705 | 4.6712 | 9.4759 | 0.1847 | 0.3747 | 4.0629 | 3.3462 | 4.0629 | 1.4427 |
|---|
| 45 | 'sub-0053' | 'cognitive' | 11.9415 | 13.2427 | 0.6882 | 0.7632 | 29.9440 | 12.9839 | 1.5382 | 0.6670 | 8.1070 | 12.2422 | 0.4672 | 0.7056 | -0.2199 | 10.0518 | -0.0113 | 0.5164 | 1.4730 | 1.4210 | 1.4730 | 1.1506 |
|---|
| 46 | 'sub-0055' | 'cognitive' | 6.1222 | 20.3210 | 0.2700 | 0.8964 | 38.7039 | 12.0307 | 1.6145 | 0.5018 | 4.6938 | 18.9980 | 0.2070 | 0.8380 | 0.8040 | 11.3858 | 0.0335 | 0.4749 | 1.3043 | 1.2509 | 1.3043 | 1.0522 |
|---|
| 47 | 'sub-0056' | 'cognitive' | 15.7066 | 17.5714 | 0.5142 | 0.5752 | 23.3121 | 17.7696 | 0.7711 | 0.5878 | 12.9655 | 17.5030 | 0.4244 | 0.5730 | 0.1885 | 17.5451 | 0.0062 | 0.5804 | 1.2114 | 1.1963 | 1.2114 | 1.0630 |
|---|
| 48 | 'sub-0057' | 'cognitive' | 22.9506 | 16.8627 | 0.9516 | 0.6992 | 52.1062 | 20.2434 | 1.6139 | 0.6270 | -7.0868 | 28.7398 | -0.2938 | 1.1917 | -10.6046 | 10.1102 | -0.3285 | 0.3131 | -3.2385 | -3.9348 | -3.2385 | 2.7637 |
|---|
| 49 | 'sub-0058' | 'cognitive' | -7.4936 | 16.5761 | -0.2724 | 0.6026 | 12.5055 | 19.9503 | 0.6387 | 1.0190 | 4.2835 | 27.2602 | 0.1557 | 0.9910 | 0.1556 | 16.7593 | 0.0079 | 0.8560 | -1.7494 | -1.2290 | -1.7494 | 0.6295 |
|---|
| 50 | 'sub-0059' | 'cognitive' | 1.1987 | 8.5587 | 0.0501 | 0.3577 | 10.2994 | 6.4084 | 0.4729 | 0.2943 | 5.8564 | 5.0230 | 0.2448 | 0.2099 | -2.4764 | 6.0788 | -0.1137 | 0.2791 | 0.2047 | 0.3207 | 0.2047 | 0.8436 |
|---|
| 51 | 'sub-0060' | 'cognitive' | 2.5446 | 18.4368 | 0.2057 | 1.4906 | 33.8178 | 7.7534 | 1.5281 | 0.3504 | 5.0787 | 12.1299 | 0.4106 | 0.9807 | -7.4629 | 11.1781 | -0.3372 | 0.5051 | 0.5010 | 0.5831 | 0.5010 | 0.8548 |
|---|
| 52 | 'sub-0061' | 'cognitive' | 24.6746 | 29.5973 | 0.6641 | 0.7965 | 64.4368 | 17.6156 | 1.7557 | 0.4800 | 9.1292 | 33.6469 | 0.2457 | 0.9055 | -3.8321 | 15.4191 | -0.1044 | 0.4201 | 2.7028 | 2.5347 | 2.7028 | 1.3358 |
|---|
| 53 | 'sub-0062' | 'cognitive' | 5.1751 | 22.1121 | 0.1821 | 0.7780 | 43.0404 | 15.3888 | 1.3952 | 0.4988 | 10.5207 | 29.5200 | 0.3701 | 1.0386 | -6.9104 | 17.6391 | -0.2240 | 0.5718 | 0.4919 | 0.5360 | 0.4919 | 0.8627 |
|---|
| 54 | 'sub-0064' | 'cognitive' | 30.5964 | 18.5409 | 1.2233 | 0.7413 | 63.3200 | 19.3213 | 1.8192 | 0.5551 | 5.2199 | 17.4498 | 0.2087 | 0.6977 | 2.1844 | 9.5380 | 0.0628 | 0.2740 | 5.8615 | 5.0799 | 5.8615 | 1.8394 |
|---|
| 55 | 'sub-0065' | 'cognitive' | 6.5333 | 11.7044 | 0.1897 | 0.3399 | 25.4020 | 19.5957 | 0.5946 | 0.4587 | 8.2201 | 9.2674 | 0.2387 | 0.2691 | -5.6883 | 13.5883 | -0.1332 | 0.3181 | 0.7948 | 0.8170 | 0.7948 | 0.9605 |
|---|
| 56 | 'sub-0066' | 'cognitive' | 0.3890 | 25.6717 | 0.0238 | 1.5693 | 23.3349 | 23.8784 | 1.1938 | 1.2216 | -1.3201 | 25.1146 | -0.0807 | 1.5352 | -4.7012 | 17.9001 | -0.2405 | 0.9158 | -0.2947 | -4.3389 | -0.2947 | 1.1137 |
|---|
| 57 | 'sub-0068' | 'cognitive' | 3.0495 | 5.3578 | 0.0558 | 0.0980 | 17.0549 | 19.7895 | 0.3170 | 0.3678 | 7.3126 | 6.5490 | 0.1337 | 0.1198 | -4.0421 | 6.2897 | -0.0751 | 0.1169 | 0.4170 | 0.4871 | 0.4170 | 0.9312 |
|---|
| 58 | 'sub-0069' | 'cognitive' | 1.7832 | 5.9193 | 0.0491 | 0.1631 | 28.5825 | 9.4910 | 0.8783 | 0.2916 | 6.1943 | 8.1693 | 0.1707 | 0.2251 | -7.1559 | 12.1381 | -0.2199 | 0.3730 | 0.2879 | 0.3869 | 0.2879 | 0.8962 |
|---|
| 59 | 'sub-0070' | 'cognitive' | 8.3779 | 9.3743 | 0.4831 | 0.5406 | 22.6325 | 13.8565 | 0.8956 | 0.5483 | 2.3835 | 7.9634 | 0.1374 | 0.4592 | 1.3415 | 10.3723 | 0.0531 | 0.4104 | 3.5150 | 2.7717 | 3.5150 | 1.3039 |
|---|
| 60 | 'sub-0071' | 'cognitive' | -5.0574 | 22.0937 | -0.3430 | 1.4985 | 3.3217 | 12.0312 | 0.2658 | 0.9628 | 17.0793 | 25.5135 | 1.1584 | 1.7305 | 1.9389 | 22.6279 | 0.1552 | 1.8107 | -0.2961 | -0.2244 | -0.2961 | 0.3044 |
|---|
| 61 | 'sub-0073' | 'cognitive' | -0.2566 | 13.4703 | -0.0114 | 0.5988 | 1.6591 | 4.8643 | 0.0777 | 0.2279 | 4.3479 | 10.4747 | 0.1933 | 0.4656 | -0.5327 | 6.0074 | -0.0250 | 0.2815 | -0.0590 | 0.1390 | -0.0590 | 0.8285 |
|---|
| 62 | 'sub-0074' | 'cognitive' | 5.8988 | 13.8170 | 0.0982 | 0.2301 | 0.2017 | 17.7597 | 0.0029 | 0.2539 | 7.1641 | 9.7417 | 0.1193 | 0.1623 | 0.9384 | 11.7742 | 0.0134 | 0.1683 | 0.8234 | 0.8450 | 0.8234 | 0.9812 |
|---|
| 63 | 'sub-0075' | 'cognitive' | 8.5262 | 18.6750 | 0.3511 | 0.7690 | 40.0914 | 19.1547 | 1.5495 | 0.7403 | -1.5377 | 21.1293 | -0.0633 | 0.8701 | 0.9779 | 18.4256 | 0.0378 | 0.7121 | -5.5446 | -17.7156 | -5.5446 | 1.4425 |
|---|
| 64 | 'sub-0076' | 'cognitive' | 0.4000 | 12.5629 | 0.0138 | 0.4336 | 37.9370 | 12.6119 | 1.3466 | 0.4477 | 21.8607 | 15.4932 | 0.7545 | 0.5348 | -3.8638 | 6.3935 | -0.1372 | 0.2269 | 0.0183 | 0.0612 | 0.0183 | 0.5778 |
|---|
| 65 | 'sub-0077' | 'cognitive' | 3.7333 | 28.6368 | 0.1489 | 1.1419 | 32.2698 | 9.7592 | 1.1618 | 0.3514 | 19.2993 | 28.4141 | 0.7696 | 1.1330 | -5.5203 | 8.0507 | -0.1987 | 0.2898 | 0.1934 | 0.2332 | 0.1934 | 0.6492 |
|---|
| 66 | 'sub-0078' | 'cognitive' | 14.4507 | 16.2990 | 0.4379 | 0.4939 | 36.9402 | 8.5801 | 1.0434 | 0.2424 | 0.7033 | 20.0649 | 0.0213 | 0.6081 | -3.7800 | 13.1893 | -0.1068 | 0.3725 | 20.5456 | 9.0708 | 20.5456 | 1.4079 |
|---|
| 67 | 'sub-0079' | 'cognitive' | 22.0580 | 20.0778 | 0.9264 | 0.8433 | 29.7945 | 19.0029 | 1.0268 | 0.6549 | 4.2137 | 12.1185 | 0.1770 | 0.5090 | 12.4726 | 15.3076 | 0.4298 | 0.5275 | 5.2348 | 4.4226 | 5.2348 | 1.6368 |
|---|
| 68 | 'sub-0080' | 'cognitive' | 7.5481 | 19.4834 | 0.1476 | 0.3810 | 26.5506 | 12.5526 | 0.6101 | 0.2885 | 11.4657 | 23.7800 | 0.2242 | 0.4650 | 3.7576 | 5.2122 | 0.0863 | 0.1198 | 0.6583 | 0.6857 | 0.6583 | 0.9374 |
|---|
| 69 | 'sub-0081' | 'cognitive' | 6.8318 | 14.4435 | 0.3807 | 0.8048 | 40.7703 | 14.3368 | 1.6788 | 0.5903 | 13.7957 | 12.6276 | 0.7687 | 0.7036 | -5.5559 | 10.0361 | -0.2288 | 0.4133 | 0.4952 | 0.5293 | 0.4952 | 0.7806 |
|---|
| 70 | 'sub-0082' | 'cognitive' | -1.5771 | 13.4873 | -0.0655 | 0.5600 | -2.4745 | 1.5171 | -0.0975 | 0.0598 | 3.3366 | 4.2286 | 0.1385 | 0.1756 | 2.5542 | 2.1366 | 0.1007 | 0.0842 | -0.4727 | -0.1331 | -0.4727 | 0.8208 |
|---|
| 71 | 'sub-0083' | 'cognitive' | 9.8813 | 11.2866 | 0.3097 | 0.3538 | 6.5073 | 8.5329 | 0.2208 | 0.2896 | 6.6828 | 9.4742 | 0.2095 | 0.2970 | -3.7943 | 6.7962 | -0.1288 | 0.2306 | 1.4786 | 1.4163 | 1.4786 | 1.0829 |
|---|
| 72 | 'sub-0084' | 'cognitive' | 2.0177 | 7.1983 | 0.1090 | 0.3890 | 15.9036 | 9.3372 | 0.8690 | 0.5102 | 1.9562 | 6.1847 | 0.1057 | 0.3342 | 4.5914 | 8.3610 | 0.2509 | 0.4569 | 1.0314 | 1.0208 | 1.0314 | 1.0030 |
|---|
| 73 | 'sub-0085' | 'cognitive' | -3.9548 | 6.8195 | -0.4664 | 0.8042 | -2.6787 | 7.1474 | -0.3623 | 0.9666 | -1.5244 | 0.6765 | -0.1798 | 0.0798 | 2.3814 | 7.9514 | 0.3220 | 1.0753 | 2.5944 | 5.6349 | 2.5944 | 0.6506 |
|---|
| 74 | 'sub-0086' | 'cognitive' | 11.3257 | 14.5792 | 0.4973 | 0.6401 | 39.3823 | 9.8551 | 1.4647 | 0.3665 | 8.8472 | 10.1065 | 0.3885 | 0.4438 | -1.7862 | 11.7341 | -0.0664 | 0.4364 | 1.2802 | 1.2517 | 1.2802 | 1.0784 |
|---|
| 75 | 'sub-0087' | 'cognitive' | 5.5927 | 34.0216 | 0.2015 | 1.2259 | 30.5186 | 20.0898 | 1.1278 | 0.7424 | 15.1966 | 31.2181 | 0.5476 | 1.1249 | -2.0262 | 9.0054 | -0.0749 | 0.3328 | 0.3680 | 0.4070 | 0.3680 | 0.7764 |
|---|
| 76 | 'sub-0088' | 'cognitive' | 15.2735 | 20.0515 | 0.3081 | 0.4045 | 27.8553 | 24.3222 | 0.6408 | 0.5596 | -3.3343 | 27.3853 | -0.0673 | 0.5524 | -5.2047 | 11.9733 | -0.1197 | 0.2755 | -4.5807 | -6.9713 | -4.5807 | 1.4024 |
|---|
| 77 | 'sub-0089' | 'cognitive' | 3.3271 | 13.3398 | 0.1783 | 0.7149 | 8.8717 | 10.7017 | 0.5689 | 0.6863 | 4.7223 | 9.1263 | 0.2531 | 0.4891 | -0.3693 | 7.5097 | -0.0237 | 0.4816 | 0.7046 | 0.7562 | 0.7046 | 0.9403 |
|---|
| 78 | 'sub-0090' | 'cognitive' | 1.8323 | 8.2062 | 0.0661 | 0.2963 | 23.5446 | 11.5257 | 0.9504 | 0.4652 | 9.1028 | 13.6951 | 0.3286 | 0.4944 | -1.2907 | 8.2869 | -0.0521 | 0.3345 | 0.2013 | 0.2804 | 0.2013 | 0.8024 |
|---|
| 79 | 'sub-0091' | 'cognitive' | 7.1400 | 14.7140 | 0.3715 | 0.7655 | 22.1368 | 18.9411 | 1.0076 | 0.8621 | 4.2521 | 15.3621 | 0.2212 | 0.7993 | 5.2955 | 14.3535 | 0.2410 | 0.6533 | 1.6792 | 1.5499 | 1.6792 | 1.1230 |
|---|
| 80 | 'sub-0092' | 'cognitive' | 24.4364 | 36.2499 | 0.6724 | 0.9975 | 49.3633 | 19.6142 | 1.1503 | 0.4571 | 11.0779 | 40.9561 | 0.3048 | 1.1270 | 8.5470 | 19.9727 | 0.1992 | 0.4654 | 2.2059 | 2.1060 | 2.2059 | 1.2817 |
|---|
| 81 | 'sub-0093' | 'cognitive' | 3.5885 | 17.9190 | 0.1273 | 0.6355 | 31.4197 | 18.3124 | 1.1219 | 0.6539 | 2.7326 | 13.0710 | 0.0969 | 0.4635 | -2.3251 | 12.5918 | -0.0830 | 0.4496 | 1.3132 | 1.2293 | 1.3132 | 1.0277 |
|---|
| 82 | 'sub-0094' | 'cognitive' | 2.9988 | 27.4864 | 0.1045 | 0.9579 | 47.9392 | 16.2255 | 1.6675 | 0.5644 | 7.9472 | 26.7297 | 0.2770 | 0.9315 | -3.3188 | 14.7081 | -0.1154 | 0.5116 | 0.3773 | 0.4469 | 0.3773 | 0.8650 |
|---|
| 83 | 'sub-0095' | 'cognitive' | 1.1787 | 10.7386 | 0.0509 | 0.4635 | 13.6428 | 14.1571 | 0.7487 | 0.7769 | 7.7632 | 7.1759 | 0.3351 | 0.3097 | -1.8000 | 15.1379 | -0.0988 | 0.8307 | 0.1518 | 0.2486 | 0.1518 | 0.7871 |
|---|
| 84 | 'sub-0097' | 'cognitive' | -2.1704 | 11.0542 | -0.1150 | 0.5858 | 16.2962 | 16.0766 | 1.0910 | 1.0763 | 15.3279 | 13.4775 | 0.8122 | 0.7142 | 8.0975 | 8.3493 | 0.5421 | 0.5590 | -0.1416 | -0.0717 | -0.1416 | 0.4883 |
|---|
| 85 | 'sub-0098' | 'cognitive' | 4.3140 | 26.4043 | 0.1215 | 0.7437 | 43.4601 | 10.8295 | 1.4573 | 0.3631 | 11.4345 | 23.8139 | 0.3221 | 0.6707 | -2.1625 | 10.5896 | -0.0725 | 0.3551 | 0.3773 | 0.4274 | 0.3773 | 0.8483 |
|---|
| 86 | 'sub-0099' | 'cognitive' | 18.8287 | 15.7938 | 0.6248 | 0.5241 | 51.0540 | 22.4104 | 1.5226 | 0.6684 | 12.9131 | 15.8510 | 0.4285 | 0.5260 | -2.7003 | 26.3129 | -0.0805 | 0.7847 | 1.4581 | 1.4252 | 1.4581 | 1.1374 |
|---|
| 87 | 'sub-0100' | 'cognitive' | 5.1873 | 14.1953 | 0.2821 | 0.7720 | 9.3438 | 14.2304 | 0.6063 | 0.9233 | 5.8956 | 14.5599 | 0.3206 | 0.7918 | -0.8069 | 15.6584 | -0.0524 | 1.0160 | 0.8799 | 0.8973 | 0.8799 | 0.9708 |
|---|
| 88 | 'sub-0101' | 'cognitive' | 15.4090 | 22.0569 | 0.5398 | 0.7726 | 51.5548 | 13.9410 | 1.7639 | 0.4770 | 5.1908 | 25.9604 | 0.1818 | 0.9094 | -1.5165 | 13.5968 | -0.0519 | 0.4652 | 2.9685 | 2.6506 | 2.9685 | 1.3029 |
|---|
| 89 | 'sub-0103' | 'cognitive' | 2.3022 | 15.4002 | 0.1300 | 0.8693 | 5.1869 | 7.5595 | 0.5995 | 0.8737 | -0.6328 | 6.9578 | -0.0357 | 0.3928 | 1.6578 | 9.7061 | 0.1916 | 1.1218 | -3.6379 | 8.9940 | -3.6379 | 1.1718 |
|---|
| 90 | 'sub-0104' | 'cognitive' | -1.3682 | 19.3069 | -0.0549 | 0.7742 | 34.9579 | 18.7939 | 1.4288 | 0.7682 | 6.5253 | 18.9035 | 0.2617 | 0.7580 | 8.3809 | 14.2706 | 0.3426 | 0.5833 | -0.2097 | -0.0489 | -0.2097 | 0.7491 |
|---|
| 91 | 'sub-0105' | 'cognitive' | 7.0253 | 14.3215 | 0.2680 | 0.5463 | 27.2273 | 13.8001 | 1.1086 | 0.5619 | 8.9893 | 15.5297 | 0.3429 | 0.5924 | -7.1603 | 10.2791 | -0.2916 | 0.4185 | 0.7815 | 0.8034 | 0.7815 | 0.9442 |
|---|
| 92 | 'sub-0106' | 'cognitive' | 15.5914 | 19.0991 | 0.3526 | 0.4319 | 55.5587 | 27.8748 | 1.3553 | 0.6800 | -7.5867 | 19.8597 | -0.1716 | 0.4491 | -5.7711 | 24.8312 | -0.1408 | 0.6058 | -2.0551 | -2.5189 | -2.0551 | 1.6326 |
|---|
| 93 | 'sub-0107' | 'cognitive' | 1.5279 | 12.3658 | 0.0668 | 0.5409 | 22.9601 | 13.5457 | 1.0439 | 0.6159 | -2.5996 | 8.8031 | -0.1137 | 0.3850 | -6.0442 | 14.1183 | -0.2748 | 0.6419 | -0.5877 | -1.5804 | -0.5877 | 1.2037 |
|---|
| 94 | 'sub-0109' | 'cognitive' | 8.9120 | 11.2881 | 0.5307 | 0.6723 | 33.3850 | 10.1569 | 1.5243 | 0.4638 | 3.4697 | 10.9438 | 0.2066 | 0.6518 | -3.2353 | 11.3228 | -0.1477 | 0.5170 | 2.5685 | 2.2176 | 2.5685 | 1.2686 |
|---|
| 95 | 'sub-0111' | 'cognitive' | 10.9712 | 16.0629 | 0.2592 | 0.3795 | 37.7058 | 14.5987 | 1.0167 | 0.3937 | 9.5472 | 13.8864 | 0.2256 | 0.3281 | -0.8567 | 6.3419 | -0.0231 | 0.1710 | 1.1492 | 1.1350 | 1.1492 | 1.0275 |
|---|
| 96 | 'sub-0112' | 'cognitive' | 13.8752 | 15.9423 | 0.4196 | 0.4821 | 42.1139 | 15.9631 | 1.1127 | 0.4218 | 4.9553 | 15.1341 | 0.1499 | 0.4577 | 6.4840 | 13.7512 | 0.1713 | 0.3633 | 2.8001 | 2.4978 | 2.8001 | 1.2346 |
|---|
| 97 | 'sub-0114' | 'cognitive' | 8.1080 | 22.9188 | 0.3274 | 0.9255 | 53.0542 | 33.2356 | 1.6818 | 1.0536 | 14.2399 | 20.0453 | 0.5750 | 0.8094 | -2.9462 | 17.1716 | -0.0934 | 0.5443 | 0.5694 | 0.5976 | 0.5694 | 0.8428 |
|---|
| 98 | 'sub-0115' | 'cognitive' | 4.1113 | 9.1313 | 0.2716 | 0.6032 | 23.0751 | 11.1181 | 1.2182 | 0.5869 | 2.4699 | 11.4893 | 0.1632 | 0.7590 | -0.1318 | 10.9337 | -0.0070 | 0.5772 | 1.6645 | 1.4730 | 1.6645 | 1.0932 |
|---|
| 99 | 'sub-0116' | 'cognitive' | 5.6911 | 23.6144 | 0.1868 | 0.7751 | 25.6251 | 10.9808 | 0.9768 | 0.4186 | 12.7619 | 18.5482 | 0.4189 | 0.6088 | 0.1074 | 10.5780 | 0.0041 | 0.4032 | 0.4459 | 0.4862 | 0.4459 | 0.8364 |
|---|
| 100 | 'sub-0117' | 'cognitive' | 3.6641 | 9.3606 | 0.1697 | 0.4334 | 14.2585 | 14.8439 | 0.9004 | 0.9374 | -0.5050 | 5.2763 | -0.0234 | 0.2443 | -0.6925 | 6.1074 | -0.0437 | 0.3857 | -7.2550 | 9.4231 | -7.2550 | 1.1977 |
|---|
| ⋮ |
|---|
pain_task = find(strcmp(beh_cueeffect.task, 'pain'));
pain_cueeffect = beh_cueeffect(pain_task, :);
% extract subject ids from contrast fMRI data object and intersect with
nRows = size(con_data_obj.image_names, 1);
sub_ids = cell(nRows, 1);
sub_ids{i} = con_data_obj.image_names(i, 1:8);
sub_ids_table = table(sub_ids, 'VariableNames', {'sub'});
common_subs = intersect(sub_ids_table.sub, pain_cueeffect.sub)
'sub-0014'
'sub-0026'
'sub-0028'
'sub-0029'
'sub-0030'
'sub-0031'
'sub-0033'
'sub-0035'
'sub-0039'
'sub-0040'
% Ensure beh_cueeffect.sub is a cell array for comparison
if ~iscell(pain_cueeffect.sub)
pain_cueeffect.sub = cellstr(pain_cueeffect.sub);
rows_to_keep = ismember(pain_cueeffect.sub, common_subs);
filtered_pain_cueeffect = pain_cueeffect(rows_to_keep, :);
% regenerate contrast filenames based on intersecting subject ids
% Initialize an empty cell array for the file paths
filteredcon_files = cell(length(common_subs), 1);
% Loop through each subject ID and construct the file path
for i = 1:length(common_subs)
filteredcon_files{i} = fullfile(mount_dir, common_subs{i}, [common_subs{i}, '_con_0020.nii']);
cue_raw_outcome = apply_nps(cue_raw_outcome.t);
NPS values for series 1
Unknown image names 17.3451
Unknown image names 35.5074
cue_z_outcome = apply_nps(cue_z_outcome_obj.t);
NPS values for series 1
Unknown image names 17.4539
Unknown image names 35.3987
cuestim_outcome_raw = apply_nps(cuestim_outcome_raw_obj.t);
NPS values for series 1
Unknown image names 6.8085
Unknown image names 49.7159
cuestim_z_outcome = apply_nps(cuestim_z_outcome_obj.t);
NPS values for series 1
Unknown image names 6.8085
Unknown image names 49.7159
cuestim_raw_outcome_reg = apply_nps(cuestim_raw_outcome_reg_obj.t)
NPS values for series 1
Unknown image names 7.5542
Unknown image names 46.9010
cuestim_raw_outcome_reg =
{2×1 double}
cuestim_z_outcome_reg = apply_nps(cuestim_z_outcome_reg_obj.t);
NPS values for series 1
Unknown image names 5.7982
Unknown image names 16.2841
cue_effects = table(cue_raw_outcome{1}(2), ...
cuestim_outcome_raw{1}(2), ...
cuestim_z_outcome{1}(2), ...
cuestim_raw_outcome_reg{1}(2),...
cuestim_z_outcome_reg{1}(2));
cue_effects.Properties.VariableNames = {'Cue (Raw)', 'Cue (Z)', 'Cue/Stim (Raw)', 'Cue/Stim (Z)', 'Cue+1/Stim+1 (raw)', 'Cue+1/Stim+1 (Z)'}
cue_effects = 1×6 table
| | Cue (Raw) | Cue (Z) | Cue/Stim (Raw) | Cue/Stim (Z) | Cue+1/Stim+1 (raw) | Cue+1/Stim+1 (Z) |
|---|
| 1 | 35.5074 | 35.3987 | 49.7159 | 49.7159 | 46.9010 | 16.2841 |
|---|